Barriers to SME Growth in Slovenia

Will Bartlett

School for Policy Studies

University of Bristol

&

Vladimir Bukvić

GEA College, Ljubljana

Slovenia

Abstract

The paper is based on the findings of a research project which aimed to identify the

critical barriers to small business growth and development in Slovenia. The key

barriers identified in the research included factors linked to the institutional

environment including bureaucracy, and to external financial constraints including

the high cost of capital. Internal organisation and resource issues, and social support

through local development coalitions were found to be less important. The research

was based upon a sample survey of small firms in Slovenia, and on an econometric

analysis of the sources of firms' growth. This provided evidence that firms' growth

was negatively linked to firms' size, and that growth was reduced by the presence of

institutional and financial barriers. On the other hand employee benefits such as

severance pay were positively linked to growth. The paper provides a possible

explanation for this unexpected finding and discusses the policy implications.

Address for correspondence:

Will Bartlett, SPS

8 Priory Rd, Bristol BS8 2QD

Tel: +44-117-9456755

Fax: +44-117-9546756

Email: will.bartlett@bristol.ac.uk

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1. Introduction: the role of SMEs in transition economies

Interest in the role of SMEs in the process of transition has developed apace in recent

years. It is now widely accepted that the SME sector can play a key role in the

process of transition. The main areas in which the sector contributes are in job

creation, innovation and the creation of competition.

Blanchard (1997) argues that the essence of transition is a reallocation of resources

from the state sector to the private sector, combined with a restructuring within firms.

The creation of new firms is a key mechanism through which the process of

reallocation can take effect. Once established, the growth of these firms provides a

further avenue through which reallocation can proceed.

The process of transition may be held up and delayed or even subverted if the

reallocation of resources from towards the private sector is blocked. One way in

which this can occur is if there are significant barriers to the entry of small firms.

Several authors have recently studied the significance of this phenomenon.

However, in most transition economies there is not an absence but rather a surplus of

new firm entry. A more serious potential problem which may hold up transition is

barriers to the growth of firms, especially the potentially dynamic fast growth firms

that will provide the largest part of future employment growth and be the seeds of the

successful large firms of the future economy.

2. Theories and empirics of SME growth

Much of the economic theory of the growth of small firms has been concerned with

the relationship between growth and firm size. The conventional wisdom in

economic theory has long held that, due to economies of scale and scope, the growth

of firms is positively related to their size. Large firms were typically expected to

have advantages over small firms and so grow more rapidly. This process was

expected to lead to a growing concentration of industry. This partly explains the

emphasis on large scale industry in the former centrally planned economies. But to

some extent it no doubt also explains the fascination of economists from both east

and west with the newly privatised firms in those countries. It was expected by

many that all that was needed to release the forces of growth was a transfer of

ownership from the state to “outside owners” who would engage in a process of

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strategic restructuring which would lead inevitably to rapid growth of the privatised

firm sector. It was also thought that the small firm sector would play a relatively

insignificant role in regeneration and transition growth (Scase, 1997). However,

these expectations were in many cases frustrated. Attention turned to imperfections

in “corporate governance” as an explanation of the poor performance of the

privatised large firms. “Insider” ownership was one culprit widely put forward to

explain the disappointing performance of the large-scale privatised sector.

The outcome may have been less puzzling if those observers had paid attention to the

growing literature on the empirical analysis of the relationship between firm size and

growth which has emerged in the West in recent years. This literature is beginning

to show a consistent negative relationship between firm size and firm growth,

spanning several studies and many countries. As Hart (2000) observes, “most

studies relating to periods since 1885 show that small firms grow more quickly than

larger firms”. In the UK, for example, Hart and Oulton (1996) studied a sample of

29,230 firms and found a negative relationship between growth and firm size, based

on a Galtonian regression, for the period 1989-1993. In the USA, Evans (1987)

studied a sample of 24,244 firms which had been in business for over seven years,

and found a similar relationship for the years 1976-1980. Alnus and Nerlinger

(2000) show the same relationship in Germany, while Farinas and Moreno (2000)

confirmed the relationship for Spanish data covering over 2,000 firms. Many other

studies have shown similar results, including those by Evans (1987a), Dunne and

Hughes (1994) and Hart and Oulsen (1998). These empirical studies confirm that in

contrast to the orthodox views, small firms grow faster than large firms.

There are several possible explanations of the reasons for the faster growth of small

firms. Small firms may grow faster than large firms because since they are initially

uncertain about their costs firms enter the market at less than minimum efficient

scale and over time grow to reach it (Jovanovic, 1982). However, as Hart has

pointed out, if this was all there was to it the dispersion of firm sizes would be very

small, whereas the reality is that the dispersion of firm sizes is large. A second

explanation relies on the theories of flexibility and adaptability of small firms,

emphasised by the students of the phenomenon of the industrial district and of the

strength of network economies which can offset the economies of scale enjoyed by

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large firms (Bartlett and Franičević, 2001). A third explanation is that large firms

suffer from diseconomies of scale. This is often linked to the increase in managerial

costs as firm size increases and the costs of coordinating across an expanding span of

control encounter limits placed by bounded rationality (Penrose, 1980). A fourth

explanation is firms react asymmetrically to exogenous shocks in the short run.

Given short run U-shaped cost curves, small firms which operate below minimum

efficient scale will expand output when prices rise, while larger firms above

minimum efficient scale will not. Conversely, small firms will not react to price falls

while large firms will reduce output. In the absence of capacity adjustments, small

firms have a bias to increase output, while larger firms have a bias to reduce it

(Johnson, Conway and Kattuman, 1999). A fourth explanation, emphasised by Hart

(2000), is the impact of the many measures introduced by Western governments to

promote and support the growth of small firms and entrepreneurship in recent

decades in those economies. This implies that the “invisible hand” of the market is

not enough to generate economic growth on its own: an activist state pursuing an

energetic enterprise policy is a key mechanism to get the most out of the market

economy system.

The stylised fact that small firms grow faster than large firms in advanced market

economies has important implications for industrial policy in transition economies.

It suggests firstly that SME development should be a central plank of industrial

policy in these economies, with the aim of expediting the reallocation of resources

from the state sector to the private sector (Levitsky, 1996; Kolodko, 2000). As the

large firm sector is being privatised and restructured, the small and medium sized

sector will need to expand and grow to generate enough jobs to absorb those laid off

as well as providing jobs for the new entrants to the labour market (Rona-Tas, 1997).

But in many transition economies, especially in south east Europe1, the small firm

sector has not grown sufficiently rapidly to prevent unemployment from rising, nor

has it fulfilled its potential as an engine of growth (Acs and Audretsch, 1993;

1 Elsewhere in Eastern Europe, there has been more success. Poland for example is a

success story in respect of SME sector promotion and development.

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Johnson and Loveman, 1995). Although large numbers of new small firms have

entered the market, as commercial laws have been reformed and markets liberalised,

they have not grown as rapidly as might have been expected from experience in

advanced western market economies. The reason is likely to be found in the barriers

to growth which persist in the transition economies (Hanley, 2000; Broadman, 2000).

As we show in the following section, these can be classified as institutional barriers,

internal organisational and resource barriers, external market barriers, financial

barriers and social barriers. In the remainder of this paper we explore the nature of

these barriers to growth and report the results of an empirical survey carried out in

Slovenia in 2000 to study the impact of these barriers on the growth of small and

medium sized firms in that country.

3. Barriers to SME growth

In most market economies, except the most flexible, and deregulated, there are

significant real barriers to both business entry and growth. The importance of the

issue in the UK for example has been highlighted in a recent report by the Federation

of Small businesses entitled “Barriers to Survival and Growth in UK Small Firms”

(FSB, 2000). It might be imagined that transition economies are likely to face even

more severe barriers to growth of SMEs. Of special importance here is the set of

barriers which hinder the growth of potentially fast growth firms (“gazelles”) which

have the greatest capacity to generate jobs and introduce innovations and new

technologies. These barriers are likely to be both internal and external to the firm.

Such barriers to growth hinder the rapid redeployment of labour from the old

unproductive large firms to the newly emerging small-scale private sector. In

consequence, growth may be below the potential of the economy, and unemployment

consequently higher than it need be. In the worst case barriers to growth may block

the transition to a competitive market economy altogether.

Of course, not all entrepreneurs seek growth, and growth is not a necessary or even

desirable objective for all SMEs. Firstly, the SME owners may have objectives other

than profit maximisation. Secondly, if profit maximising, they may have already

reached the minimum efficient scale of business activity (small retail shops, repair

shops and so on). Therefore a lack of growth on its own does not necessarily

indicate the presence of significant barriers to growth. This implies the need for a

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benchmark model of growth against which the impact of perceived barriers to growth

can be identified and measured.

In our research we distinguish between institutional barriers (including the legislative

framework, the degree of corruption and bribery a firm encounters), barriers due to

the external market position of a firm (the sector in which the firm operates, the

degree of competition, whether a firm is facing strategic behaviour by competitors,

extent of network alliances to support growth), financial barriers (including

availability and cost of capital and finance), internal organisational barriers

(including managerial capacity and capability, objectives of firm, principal-agent

difficulties, skills), and social barriers (to do with the support, or lack of it, from local

actors and agencies).

Institutional barriers

The institutional framework within which firms interact with customers, government

and each other can have a profound influence on firms’ economic performance.

Business growth is often considered to be at risk from heavy-handed bureaucracy, in

both West and East European economies. Official and unofficial institutions each

play a part in this. An unsuitable tax system and various discriminatory legal

regulations can represent a severe burden for SMEs in many SEE countries.

Complicated laws, rules and regulations concerning companies can be especially

tough on small and growing companies. Over-regulation of the company sector in

market economies provides an incentive for entrepreneurs to seek ways to evade

regulations leading to the growth of the grey economy. It also provides incentives to

them to devote resources to influencing the regulatory environment in their own

favour, encouraging “unproductive entrepreneurship” (Baumol 1990). The

uncertainty resulting from unofficial institutions of the grey economy, and the

uncertain effects of interest group lobbying to influence regulatory outcomes may

reduce productive investment and slow down growth. In the worst case, the relative

newness of market institutions and legislation, and the legacy of the culture of

connections inherited from the communist past, may encourage the growth of bribery

and corruption (Schleifer and Vishny, 1993). This may further increase the

uncertainties and costs of carrying out business, and reduce the growth of firms. In

addition, powerful large firms, whether recently privatised or not, whose managers

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have good political connections, may also employ a variety of tactics to reduce the

growth of smaller firms, from strategic pricing policies to outright threats verging on

criminal behaviour. These institutional factors may increase transaction costs facing

SMEs, and hinder the transition to a competitive market economy.

Barriers internal to the firm

In addition to resource shortages and capacity limitations, an important set of internal

barriers to growth is related to the whole issue of human resource management and

the conditions concerning the hiring and firing of labour. Where there are limitations

of the use of fixed-term labour, where long advance notification of layoff is required,

where there are high mandatory severance payments which increase the cost of

dismissal, and where taxes and contributions on labour are excessive, then

entrepreneurs may be reluctant to expand their activities if this would require that

they take on new permanent employees. A key internal constraint on growth of

SMEs is a reluctance or inability of owner managers to diversify control over

business functions to professional managers (Storey 1994). In some transition

economies of Southeast Europe (SEE) this tendency may be magnified by a lack of

skilled managers, as well as an absence of business skills in the areas of marketing

and business development. The strength and salience of internal barriers is likely to

vary with the size of the firm. In the early stages of a firm’s growth, an owner

manager can cope alone with many of the areas of management such as finance,

human resources, marketing, and product development. However, once a firm has

reached a certain size, or stage in its life cycle, there is a need to professionalise the

management function if a firm is to continue to grow.

External barriers

Economists have long debated the existence of barriers to entry, which vary

depending on the degree of competition in the market and the sector of activity.

Barriers to growth may also be linked to the market environment in which firms are

placed. Factors such as low demand for the product, access to raw materials,

difficulties in exporting, public procurement rules and the late payment of bills by

business customers and even the government can all obstruct the growth of firms.

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Financial barriers

In a recent working paper of the EBRD, Francesca Pissarides (1998) has argued that

“the findings of [recent] analysis confirmed the belief that credit constraints

constitute one of the main obstacles to growth of SMEs” and indicated that “this

encouraged the EBRD to tailor its financial instruments … to the ability of the local

financial system to assume key responsibilities”. These credit constraints operate in

a variety of different ways. In most SEE countries, an underdeveloped capital

market forces entrepreneurs to rely on self-financing or borrowing from friends and

relatives. Pissarides also points to the lack of equity capital and lack of access to

long term credits for SMEs, so that small firms are forced to rely on high cost short

term finance. Financial barriers, which affect SMEs, include the high cost of credit,

relatively high bank charges and fees, high collateral requirements, and a lack of

outside equity and venture capital. Often, domestic banks are orientated to providing

loans to insolvent large enterprises. Information asymmetries between lenders and

borrowers make it hard for banks to determine the real value of a project, and lead to

credit rationing (Stiglitz and Weiss 1981). The high risk of credit to SMEs with

information asymmetry may explain the relatively high interest rates charged to those

borrowers, and the demands made on SMEs by banks for high collateral and loan

guarantees. Nevertheless, entrepreneurs may be reluctant access formal sources of

outside equity capital which dilutes their control of the firm (an issue which is also

relevant in developed economies – Hamilton and Fox 1998).

Social barriers

Recent research in the field of economic sociology has emphasised the importance of

social capital, trust and network ties between entrepreneurs as factors stimulating the

development of the SME sector (Grabher and Stark 1997; Raiser 1999). Without a

degree of trust between business partners, the parties to a transaction will feel

exposed to opportunistic behaviour which will either raise the transactions costs of

doing business or even prevent the transaction being carried out altogether. In some

SEE economies these problems seem to have been addressed by narrowing down the

range of social ties to relatively narrow ethnic or family groups. There is an absence

of open networks in which economic agents can place trust in anonymous trading

partners or in casual acquaintances. The reliance on personal connections replaces

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the anonymous market transaction as a basis for doing business. Clientelism,

paternalism and corruption can flourish in such an atmosphere.

Small firms may need an institutional support network to overcome some of these

(and other previously mentioned) barriers to growth. Local enterprise agencies can

ideally provide much needed support to new and growing SMEs in the form of

provision of information, advice and training services (“real services”). These

services may be a more effective way of overcoming the barriers to SME

development than the provision of financial assistance alone. But there are many

issues, which need to be addressed in making such institution-building policies

successful. A key issue is the role of the state in supporting them. Too close a link

to the state may lead to suspicion and mistrust by potential SME clients. Yet the

support institutions may not be sustainable propositions if transformed into private

companies and left to rely on the market alone for their future survival (Bateman

1999).

This suggests that an approach based on a public/private partnership approach may

be needed to underpin a sustainable and responsive institutional support structure

(Franičević and Bartlett, 2000). Alternatively the re-invention of the Local Authority

as the principal locus for SME support has been proposed by Bateman (2000), while

others have emphasised the importance of the creation of Local Development

Coalitions to encourage a user-oriented and participative approach to SME support

services (Bukvić, Krć, Mayr, Penca and Rus, 2000).

4. SME growth and SME policy in Slovenia

The importance of social ties and business networking for reducing the social

barriers to SME development has been emphasized in the Slovenian approach to

SME policy. The policy approach is based upon the hypothesis that SME

development can be promoted by the activities of local actors and development

coalitions including: SME development agencies, local governments, chambers of

commerce, business associations, entrepreneurs associations and clubs, local NGOs,

local banks, colleges & universities, and networks of firms (business-to-business

support). Thus, in contrast to other SEE countries, a much more supportive

institutional framework has been in place in Slovenia for since the early 1990s.

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Early initiatives were coordinated through a Ministry for Small Business, later

absorbed into the Ministry of Economic Affairs as the Small Business Development

Centre (SBDC). The SBDC has established a small business development network.

Its membership includes the Slovenian Business Innovation Network comprising 210

promotional and innovation centres, the Association of Business Consultants, the

Slovenian Business Incubator Group linking 17 business incubators, the Slovenian

Association for Venture Capital, linking 15 risk capital funds and 42 municipal

funds, and the Association of Business Clubs and Societies with 12 member

organisations. The network has been criticized for a lack of coordination between the

members (Glas 1996). In 1996 therefore, a new bottom up approach was initiated in

which coalitions of local partners were invited to bid for funds to establish Local

Business Centres. The role of these local centres is to act as one-stop shops for

business advice and training. In addition a number of local guarantee funds and

venture capital funds have also been established.

Although this approach does not necessarily address the full range of concerns which

are encompassed by the term ‘social capital’, its relative success indicates that it may

be a way forward for other SEE countries, beyond the ‘finance first’ dictum

promoted by international financial institutions such as the EBRD. Our empirical

research allows us to shed some light on these competing claims concerning the

relative merits of different approaches to SME policy in Slovenia.

5. The ACE97 SME survey in Slovenia

The research was designed to uncover the extent to which SME policies in Slovenia

have succeeded in dealing with barriers to growth facing SMEs, to determine the

main types of barriers which continue to hinder transition and development, and to

provide pointers to successful experience which could be useful in comparable

economies elsewhere in Southeast Europe. The first stage of the research has

involved a sample survey of SMEs, which is to be followed up by a set of intensive

case studies of fast and slow growth firms. The survey covered 173 small and

medium sized firms in all sectors of the Slovenian economy except agriculture. It

was based on an earlier survey carried out in 1993, which collected information

about small firms in Slovenia at an earlier stage of transition (Bartlett and Prašnikar,

1995; Bartlett, Prašnikar and Valenčić, 1995). The sample was random with a

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number of quotas including a purposeful under-sampling of firms in the trade sector

(limited to a maximum of 30% of the total sample). The sample was also restricted

to firms with at least 2 employees but no more than 250. This was done to avoid

swamping the sample with a large number of micro firms, and to capture medium

sized firms as well as smaller firms in the sampling frame. The data were collected

by personal interviews with owners and managers of the selected firms in the autumn

of 2000. Comparable surveys were also carried out in Bosnia and Macedonia, the

results of which will be reported in later papers.

6. Survey findings

Employment growth, size and sector

The surveyed firms had a mean size of just over 18 full time employees, with a

median size of 5 (see Appendix Table 1). Of the 167 firms for which data on

employment were recorded in both 1997 and 1999, 65 had expanded employment

over the three years, 70 had stayed at the same size and 32 had reduced employment.

The mean size of the growing firms was just under 15 employees, while the mean

size of the shrinking firms was just over 46 employees. Clearly the smaller firms in

the sample were delivering better economic performance than the larger (medium

sized) firms. The mean size of firms which recorded no change in employment size

was 8.5. This indicates that the very smallest firms are not so likely to expand

employment as firms in an intermediate range. The differences in average size of

firms in these three groups was significant at the 1% level, with a F statistic of 19.15.

The data shown in Table 2 indicate that firms in the manufacturing and construction

sector were more likely to be among the group of growing firms than firms in the

services, retail and wholesale sectors. In manufacturing, over 25% of firms were

growing compared to only 20% of the whole sample. On the other hand,

manufacturing firms were also most likely to be among the group of shrinking firms.

Over one half of firms in the services, retail and wholesale sectors remained stable

over the three years between 1997 and 1999, neither gaining nor losing employees.

The differences among groups was significant at the 10% level with a Chi2=16.04

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Barriers to growth

The survey asked the respondents to indicate the severity of a number of barriers to

business expansion. The barriers were placed in five groups covering (a)

institutional, (b) internal organisation and resources, (c) barriers external to the firm,

(d) finance and (e) social barriers. Altogether, 56 potential barriers to expansion

were identified and included in the questionnaire. Table 3 to Table 7 in the

Appendix presents the key findings of the survey concerning the barriers which the

sample firms faced, grouped in problem areas covering institutional, internal,

external, financial and social barriers.

Among the institutional barriers, the general problem of too much bureaucracy and

the specific problem of too many licenses needed rank the most important, with 39%

and 37% of firms viewing these as “very important” barriers to business expansion

(i.e. response code=5 on a scale 1-5). Among internal barriers, the problem of large

severance pay clearly ranks as the most important barrier with 47% of firms

regarding this as “very important”. Among external barriers, late payment of bills is

ranked most highly with 49% of firms viewing this as a “very important” problem.

Among financial barriers, the high cost of credit and loans and high collateral

requirements are ranked the most serious barriers, with 44% and 41% of firms

respectively viewing these as “very important”. Finally, among social barriers, a

lack of state support is seen as the most serious, with 28% regarding this as a “very

important” barrier to business expansion. Clearly, overall, social barriers are seen as

less serious than the other types of barriers which each have at least one issue which

around 40% of firms of more find an extremely serious barrier to growth. This may

reflect success in the Slovenian efforts to reduce social barriers by setting up Local

Development Coalitions to support SME growth.

Table 8 presents the most problematic barriers to business expansion facing

Slovenian SMEs, ranked by the incidence of very high barriers. Of these, two are

from the group of institutional barriers, one, from the group of internal barriers, two

are external barriers and three are financial barriers. Financial barriers, as predicted

by Pissarides (1999), are highly important barriers but do not top the list. Late

payment of bills and large severance payments, precede the high cost of loans as the

key barriers facing SMEs in Slovenia.

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But do these barriers have a real impact on the growth of firms? It may be that the

subjective estimates of the respondents to the survey are misconceived and do not

reflect reality. Survey research is beset by the problem of subjectivity of

respondents’ replies to questions. Pissarides, Singer and Svejnar (2000) study the

determinants of a similar set of perceptions about barriers to growth in their study of

two samples of SMEs in Russia and Bulgaria. In this paper, in order to test the

hypothesis that the five groups of barriers have real effects on firms’ growth, we

developed a model explaining firm growth based upon the standard approach in the

literature which was discussed above, namely the firm-size growth relationship.

7. Barriers to growth in Slovenia: a regression model

In our econometric estimates and test of the hypothesis that the various types of

barriers reduce potential growth of SMEs we first estimated the growth-size, and

growth-size-age relationships for our sample. We then supplemented this basic

model with the barriers to growth reported by our respondents. Based on the

assumption that the reported importance of a barrier is strongly correlation to its real

strength, we expected that strong barriers would reduce firms’ predicted growth rates

from the basic benchmark model estimated in the first stage. We were interested in

estimating the size of these effects and identifying the key variables which policy

makers would have to influence to improve the growth of the SME sector. The

empirical results indicated that both the growth-size model and the growth-size-age

model fit the data well.

1) ℓn (employment growth) = -0.139 – 0.493* ℓn(employment)

(0.719) (5.95)**

22=0.35; F=35.4**

In equation (1) the natural log of employment growth between 1997 and 1999 was

regressed on the natural log of employment size in 1997. Taking logs of the data

transformed the skewed size data into a normal distribution. Of course, it means that

only firms which experienced positive growth are included in the estimates (N=65).

The results indicate, in line with most comparable studies, that there is a negative

relationship between growth and size of firm. The coefficient on size is significant at

the 1% level. The coefficient is negative, confirming that smaller firms grow faster

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than larger firms. The size of the coefficient indicates that a 1% increase in firm size

brings about a 0.5% decrease in the rate of growth. Variations in the size of firms

explains 35% of the variation in firms’ growth..

2) ℓn (employment growth) = -0.554 – 0.435* ℓn (employment) – 0.37* ℓn (firm

age)

(1.45) (5.09)** (2.09)*

22=0.38; F=20.3**

The second regression supplements the first by the age of firms since their start up.

This is justified by the assumption of learning effects. Following Jovanovic (1982),

it is argued that firms learn about their real efficiency and costs over time. The

argument is that there are diminishing returns to learning as time goes by, and so

there are diminishing opportunities for growth as firms age. This relationship is

borne out by the estimates in equation (2). The coefficient of the natural log of firm

age is negative and significant at the 10% level.

A basic issue which we had to deal with in developing the empirical research was the

selection of relevant variables from each of the groups of barriers. Owing to the high

degree of collinearity within the groups, we decided to select, for inclusion in the

model, those barriers which the highest proportion of respondents regarded as “very

important”. The results of this exercise are reported in Table 9 in the Appendix. In

the first column the benchmark equation (2) is supplemented by the inclusion of

dummy variables for the effects of bureaucracy, severance pay, late payment of bills,

high cost of credit and the support of the local authority. The latter was chosen in

preference to the more ambiguous “support of the state” in order to test the

proposition that “local development coalitions” are a useful policy instrument to

promote SME growth. The dummy variables take a value of “1” if the respondent

reported the respective barrier as “very important”, else “0”. A negative coefficient

on the dummy therefore indicates that the barrier reduces growth, a positive

coefficient that it increases it. A further dummy variable, “university education” is

included to indicate a salient characteristic of the entrepreneur. It takes the value of

“1” if the respondent has had a university education, and “0” if not. Several other

qualitative variables from the survey were also included in various estimations of the

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model. Only education level turned out to be a significant (negative) determinant of

firm growth.

Equation (8b) in Table 9 indicates that growth is lower in firms which experience

severe problems with bureaucracy, and for whom the high cost of credit is a serious

issue. The importance of the negative influence of bureaucracy on growth supports

the institutionalists, while the negative influence of the cost of capital supports those,

like Pissarides (1999), who argue that financial barriers are key obstacles to private

sector development and transition in Eastern Europe. The age of the firm, late

payment of bills, support of the Local Authority, and education are not significant

explanatory variables in this regression model. The raw responses to the survey

indicated already that entrepreneurs do not experience a serious lack of Local

Authority support. The regression results further indicate that even where this is a

serious problem, the real impact on growth is in fact negligible. Further investigation

of the reasons for this would be warranted. Does it mean the Slovenian policy to

support SMEs locally is successful, or does it mean that Local Authorities support is

irrelevant to SMEs?

Unexpectedly, severance pay as a perceived barrier has a significant positive

coefficient. This can be explained as follows. Suppose a firm is very worried by

severance pay obligations. It should do all it can to avoid employee lay-offs. One

strategy would be to strive for growth, as this was lay-offs can be avoided. Thus, the

results of the regression model indicate that severance pay may inadvertently be a

stimulus to growth, rather than a genuine barrier.

Late payment of bills has no significant effect on growth and was dropped from the

equation in the second estimation, equation (9b). In this model education turns out to

be a significant explanatory variable, but with a negative sign, indicating that higher

education is not a prerequisite of successful entrepreneurship. In fact, if the results

of this regression model are to be believed, it implies quite the opposite: firms whose

owners have a university degree have lower rates of growth than other firms. A

similar result was observed in a study of small firm growth in the UK service sector

(Johnson, Conway and Kattuman, 1999). They observe that “it is possible for the

owners and employees to be overqualified in a way which generates a level of

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frustration that is inimical to growth” and which outweighs the otherwise expected

positive human capital effects of education.

Equations (9c) and (9d) drop the insignificant firm age and local authority variables.

The resulting model (9d) indicates that, given the size of firms, the variables

“bureaucracy”, “cost of capital” and “education” all have negative influences on firm

growth, and that “severance pay” has a positive influence.

But these equations do not take into account possible interaction effects of the

dummy variables with size and age of firm. Equations (11c) and (11b) make up for

this by introducing three dummy variables X9A (ℓn size x cost of capital), X2I (ℓn

size x severance pay) and Z1A (ℓn age x bureaucracy). These were identified by a

number of experiments with the regression model using the procedure of backward

elimination. The results indicate that the cost of credit has a more serious negative

impact on growth for larger firms compared to smaller firms. The perception of

severance pay as a serious barrier is a more effective stimulus to growth in larger

compared to smaller firms. The impact of bureaucracy on growth varies according to

the age of firms, with older firms being more adversely affected by bureaucratic

obstacles to growth than younger firms. The coefficients on the interaction terms are

all highly significant at the 5% level. The equation residuals are normally distributed

in all estimations. The equations explain almost 50% of the variation in employment

growth among SMEs.

8. Policy conclusions

International organisations have been increasingly engaged in the development of the

small business sector in Slovenia, as in other transition economies in Central and

Southeast Europe. A view has arisen that financial barriers present the most severe

obstacles to SME development in these countries (Pissarides 1998). This position

has been stressed by the international financial institutions such as the EBRD and the

World Bank. Other non-financial organisations such as the PHARE programme

have stressed the importance of non-financial barriers, which are either external to

the firm (such as the business and regulatory environment) or internal to the firm

(such as lack of managerial skills, information and training). The World Bank has

characterised the different types of actions needed to eliminate these various barriers

17

as three “pillars” of SME support (World Bank 2000). The first pillar involves

inputs of finance through SME credit lines, development of micro-finance banks, or

setting up equity capital funds. The second pillar involves actions designed to

establish “fair and transparent” tax systems and improvements to the regulatory

framework. The Investment Compact proposed by the OECD and the establishment

of Business Advisory Councils, are measures within the Stability Pact designed to

address these issues of the business and institutional environment within which

SMEs operate. The third pillar involves the creation of supportive institutions and

support networks. For example, the PHARE programme of technical assistance has

been active in setting up enterprise agencies such as the NEPA in Macedonia and

other agencies and training programmes to support SME development through the

provision of “real services” in the form of information, advice and training.

Our research findings indicate that the first pillar focus on finance may be well

directed. Even in Slovenia, one of the more developed transition economies, SMEs

experience financial barriers to growth. In our regression analysis the experience of

problems with the high cost of capital was one of the variables which had a

significant negative impact on the growth of employment, especially for larger firms.

Other related financial issues, including high collateral requirements and high bank

charges were considered to be important obstacles by the firms in the survey.

Second pillar issues connected with the institutional environment were also

problematic for SMEs. In particular the experience of high levels of bureaucracy

was shown to lead to lower growth, especially for older firms. Specific related issues

such as a requirement for too many licences were also important for a large

proportion of firms, as were tax issues including social security payments and profits

taxes. However high levels of taxation did not significantly reduce growth rates.

This is line with research carried out in the UK which has shown that the tax cuts

implemented in the 1980s had no effect on business growth. Entrepreneurs preferred

to increase consumption rather than investment when taxes were cut. Third pillar

issues related to the social support for SME development did not pose a great

problem for SMEs in Slovenia. This may reflect the relative success of existing local

development coalitions in support of entrepreneurial activity. Overall, financial and

institutional problems such as bureaucracy, rather than internal organisational

18

problems or problems with the provision of “real services”, seems to be the most

pressing SME policy issues in Slovenia.

The research also revealed some unexpected results. The most widely perceived

barriers to business growth were late payment of bills by customers, and large

severance payments. However the regression results showed that late payment of

bills had little influence on the actual growth of firms. It may be that this is more of

a nuisance than a serious obstacle to economic activity. Surprisingly, firms which

experienced severance pay as a serious problem appeared to have higher rates of

growth than other firms. The explanation for this may be that this factor acts as a

spur to growth rather than a barrier. Growth based strategies are clearly one way that

an entrepreneur can avoid large severance payments. This has obvious implications

for policy makers, who should not yield to calls from business lobbies to reduce the

level of severance pay and other employee benefits on the grounds that this would

improve economic efficiency.

Finally there are a number of cautions which need to indicated and a number of areas

of future research which the present study suggests. The main caution in interpreting

the results of the regression equations is that they are not generalisable to all firms.

Strictly speaking they are applicable only to firms which are in any case growing.

They do not encompass non-growth or shrinking firms. A wider analysis of the

barriers to all firms, whether growing or not, will be reported in a subsequent paper.

Further research is also needed into differences in barriers to growth facing different

sectors of the economy, and further detailed analysis of the survey data to encompass

other dimensions of interest including differences between innovative and non-

innovative firms, and firms engaged in various networking activities including

subcontracting, both of these dimensions are captured in the survey results.

19

Acknowledgements

The research on which this paper is based was supported by the PHARE ACE 97

Programme grant No. P97-8089-R. We are grateful to Matjaž Krć, Branko Mayr,

Primož Penca, and Andrej Rus for their assistance in gathering information and for

helpful discussions and criticisms of the themes of this paper. Any errors or

omissions are, however, our own responsibility.

20

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23

APPENDIXTable 1: Number full time employees 1997 by employment growth class

Employment growth class Mean Median % of firms. N

Shrinking 46.34 14.00 19.6% 32

No growth 8.47 3.00 41.8% 70

Growing 14.71 6.00 38.6% 65

Total 18.16 5.00 100% 167

F=19.15***

Table 2: Employment growth by sector (% of firms)

Shrinking No growth Growing Total N

Manufacturing 25.6% 25.6% 48.7% 100% 39

Services 13.7% 50.7% 35.6% 100% 73

Construction 33.3% 16.7% 50.0% 100% 12

Retail 21.4% 50.0% 28.6% 100% 14

Wholesale 15.8% 52.6% 31.6% 100% 19

Total 19.6% 41.8% 38.6% 100% 158

Pearson χ 2=16.04*

Table 3: Institutional barriers to growth

Very high barrier (%) Mean score (Scale 1-5)

Bureaucracy 39.4 3.68

Too many licences 37.3 3.64

Accounting standards 26.0 3.21

Licenses refused 24.0 3.16

Public procurementregulations

21.6 2.81

Lack of support services 15.5 2.81

Need for certificates 14.8 2.66

Lack of market information 12.4 2.69

Lack of finance information 11.2 2.76

Threats from competitors 9.5 2.17

Environmental regulations 8.9 2.34

Need to bribe officials 4.4 1.93

24

Table 4: Internal barriers to growth

Very high barrier (%) Mean Score (Scale 1-5)

Large severance pay 47.1 4.16

High labour costs 22.7 3.31

High dismissal costs 18.9 2.64

Long notice layoff 17.7 2.62

Family labour shortage 15.9 3.07

Limits on fixed term workers 15.7 2.73

Lack space 14.6 2.44

Lack capacity 10.6 2.44

Lack management time 8.8 2.50

Low skills labour 7.7 2.32

Poor labour relations 7.6 2.02

Poor quality equipment 6.4 2.21

Lack training opportunities 4.7 2.14

Labour shortages 2.3 1.47

Table 5: External barriers

Very high barrier (%) Mean Score(Scale 1-5)

Late payment 49.1 3.92

High social security payments 39.2 3.84

High profits tax 36.8 3,60

High income tax 25.7 3.21

Lack of market demand 19.2 3.06

Access raw materials 6.4 1.97

Export difficulties 4.2 1.77

25

Table 6: Financial barriers to growth

Very high barrier (%) Mean Score(Scale 1-5)

Cost of credit 44.2 3.87

High collateral requirements 41.1 3.71

Bank charges 30.0 3.41

Bank bureaucracy 26.4 3.16

Banks ignore SME 23.4 2.79

Long time to get loan 22.8 2.90

Cost to prepare business plan 15.7 2.86

Lack access venture capital 15.6 2.77

Lack access equity capital 15.1 2.76

Refusal of bank finance 11.2 2.20

Table 7: Social barriers to growth

Very high barrier (%) Mean Score(Scale 1-5)

Lack of state support 28.1 3.25

Lack of support from LA 21.1 2.90

Lack of support from Chamber 16.5 2.81

Lack support business assoc. 11.2 2.56

Lack of consultancy services 11.1 2.53

Lack of trust in society 10.7 2.48

Lack foreign partners 10.6 2.28

Lack support friends & family 5.3 1.72

26

Table 8. Top Ten Barriers to Business Expansion: Slovenia 2000

Barrier Very high barrier (%) Mean Score(Scale 1-5)

Late payment of bills (c) 49.12 3.92

Large severance payments (b) 47.06 4.16

Cost of loans (d) 44.19 3.87

High collateral payments (d) 41.07 3.71

Too much bureaucracy (a) 39.41 3.68

High social security payments (c) 39.18 3.84

Too many licences needed (a) 37.28 3.64

High profits tax (c) 36.84 3.60

Employment laws (a) 31.80 3.45

High bank charges (c) 30.00 3.41

Scale: 1=not important to 5=very important

27

Table 9: OLS regression; dependent variable: ℓn (employment growth)

8b 9b 9c 9d 11c 11b

ℓn (employment) -0.464

(5.10)**

-0.467

(5.23)**

-0.467

(5.27)**

-0.512

(6.11)**

-0.529

(5.21)**

-0.517

(5.80)**

ℓn (age of firm) -0.270

(1.44)

-0.257

(1.43)

-0.259

(1.45)

Bureaucracy -0.347

(1.79)*

-0.343

(1.79)*

-0.341

(1.80)*

-0.340

(1.77)*

Severance pay 0.340

(1.80)*

0.345

(1.84)*

0.347

(1.88)*

0.401

(2.20)**

-0.096

(0.256)

Late payment 0.055

(0.28)

Cost of credit -0.405

(1.97)*

-0.397

(1.96)*

-0.387

(2.07)**

-0.417

(2.22)**

Local Authority 0.018

(0.08)

0.030

(0.13)

Universityeducation

-0.327

(1.63)

-0.334

(1.70)*

-0.336

(1.72)*

-0.338

(1.72)*

-0.374

(1.96)*

-0.364

(1.97)*

X9A

(Cost of credit x ℓnsize)

-0.200

(2.58)**

-0.199

(2.59)**

X2I

(Severance pay x ℓnsize)

0.231

(1.45)

0.195

(2.65)**

Z1A

(Bureaucracy x ℓnage)

-0.184

(2.15)**

-0.187

(2.24)**

Constant 0.670

1.58

0.666

(1.59)

0.671

(1.62)

0.181

(0.74)

0.248

(0.96)

0.210

(0.99)

22=0.43F=6.9**

22=0.44F=8.0**

22=0.45F=9.5**

22=0.44F=10.7**

22=0.47F=10.2**

22=0.47F=12.4**

Note: Bureaucracy, severance pay, late payment, cost of credit, local authority, universityeducation, are dummy variables, equal to 1 where the respective barrier to firm’s expansionis recorded as 5 on a scale of 1=not important to 5=very important; values 1 to 4 are codedas “0”